Online expert-based prediction for cognitive radio secondary markets.
Resumen:
The growing importance of wireless communications drives an increasing interest in dynamic access to spectrum resources. This requires efficient management policies that allow spectrum sharing between licensed primary users (PU) and unlicensed secondary users (SU). On such scenario, PUs shall preserve their usage priority right over any SU. Also, no SU shall interfere on any PU. Technical viability can be achieved through Cognitive Radio devices that adjust their operating parameters adaptively. After discussing several economic and technical models to achieve efficient spectrum sharing, we propose an on-demand secondary market model regulated by a spectrum broker who controls resource allocation. This model provides economic incentives for both kind of users to cooperate: SUs are charged by the broker on behalf of PUs for resource utilization but are indemnified if expelled to ensure PU priority. We describe the main characteristics of such a system and address the question of what allocation decisions should the broker take in order to achieve economic benefit regardless of users behavior. Several online expert-based no-regret algorithms are proposed to guide the decision taking process and evaluated under different user behavior patterns. Their results are compared with the ones achieved by dynamic programming to assess its convenience.
| 2020 | |
|
Resource management Economics Biological system modeling Real-time systems Cognitive radio Prediction algorithms Adaptation models Access control Dynamic spectrum access Decision-making Communication system economics |
|
| Inglés | |
| Universidad de la República | |
| COLIBRI | |
| https://hdl.handle.net/20.500.12008/47509 | |
| Acceso abierto | |
| Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0) |
| _version_ | 1877555085926465536 |
|---|---|
| author | Vanerio, Juan Martín |
| author2 | Larroca, Federico |
| author2_role | author |
| author_facet | Vanerio, Juan Martín Larroca, Federico |
| author_role | author |
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| bitstream.checksumAlgorithm.fl_str_mv | MD5 MD5 MD5 MD5 MD5 |
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| collection | COLIBRI |
| dc.contributor.filiacion.none.fl_str_mv | Vanerio Juan Martín, Universidad de la República (Uruguay). Facultad de Ingeniería. Larroca Federico, Universidad de la República (Uruguay). Facultad de Ingeniería. |
| dc.creator.none.fl_str_mv | Vanerio, Juan Martín Larroca, Federico |
| dc.date.accessioned.none.fl_str_mv | 2024-12-12T14:58:25Z |
| dc.date.available.none.fl_str_mv | 2024-12-12T14:58:25Z |
| dc.date.issued.none.fl_str_mv | 2020 |
| dc.description.abstract.none.fl_txt_mv | The growing importance of wireless communications drives an increasing interest in dynamic access to spectrum resources. This requires efficient management policies that allow spectrum sharing between licensed primary users (PU) and unlicensed secondary users (SU). On such scenario, PUs shall preserve their usage priority right over any SU. Also, no SU shall interfere on any PU. Technical viability can be achieved through Cognitive Radio devices that adjust their operating parameters adaptively. After discussing several economic and technical models to achieve efficient spectrum sharing, we propose an on-demand secondary market model regulated by a spectrum broker who controls resource allocation. This model provides economic incentives for both kind of users to cooperate: SUs are charged by the broker on behalf of PUs for resource utilization but are indemnified if expelled to ensure PU priority. We describe the main characteristics of such a system and address the question of what allocation decisions should the broker take in order to achieve economic benefit regardless of users behavior. Several online expert-based no-regret algorithms are proposed to guide the decision taking process and evaluated under different user behavior patterns. Their results are compared with the ones achieved by dynamic programming to assess its convenience. |
| dc.format.extent.es.fl_str_mv | 12 p. |
| dc.format.mimetype.es.fl_str_mv | application/pdf |
| dc.identifier.citation.es.fl_str_mv | Vanerio, J. y Larroca, F. "Online expert-based prediction for cognitive radio secondary markets". IEEE Transactions on Cognitive Communications and Networking. [en línea]. 2020, vol. 6, no. 1, pp. 340-351. |
| dc.identifier.issn.none.fl_str_mv | 2332-7731 |
| dc.identifier.uri.none.fl_str_mv | https://hdl.handle.net/20.500.12008/47509 |
| dc.language.iso.none.fl_str_mv | en eng |
| dc.publisher.es.fl_str_mv | IEEE |
| dc.relation.none.fl_str_mv | IEEE Transactions on Cognitive Communications and Networking, vol. 6, no. 1, mar 2020, pp. 340-351. |
| dc.rights.license.none.fl_str_mv | Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0) |
| dc.rights.none.fl_str_mv | info:eu-repo/semantics/openAccess |
| dc.source.none.fl_str_mv | reponame:COLIBRI instname:Universidad de la República instacron:Universidad de la República |
| dc.subject.es.fl_str_mv | Resource management Economics Biological system modeling Real-time systems Cognitive radio Prediction algorithms Adaptation models Access control Dynamic spectrum access Decision-making Communication system economics |
| dc.title.none.fl_str_mv | Online expert-based prediction for cognitive radio secondary markets. |
| dc.type.es.fl_str_mv | Artículo |
| dc.type.none.fl_str_mv | info:eu-repo/semantics/article |
| dc.type.version.none.fl_str_mv | info:eu-repo/semantics/publishedVersion |
| description | The growing importance of wireless communications drives an increasing interest in dynamic access to spectrum resources. This requires efficient management policies that allow spectrum sharing between licensed primary users (PU) and unlicensed secondary users (SU). On such scenario, PUs shall preserve their usage priority right over any SU. Also, no SU shall interfere on any PU. Technical viability can be achieved through Cognitive Radio devices that adjust their operating parameters adaptively. After discussing several economic and technical models to achieve efficient spectrum sharing, we propose an on-demand secondary market model regulated by a spectrum broker who controls resource allocation. This model provides economic incentives for both kind of users to cooperate: SUs are charged by the broker on behalf of PUs for resource utilization but are indemnified if expelled to ensure PU priority. We describe the main characteristics of such a system and address the question of what allocation decisions should the broker take in order to achieve economic benefit regardless of users behavior. Several online expert-based no-regret algorithms are proposed to guide the decision taking process and evaluated under different user behavior patterns. Their results are compared with the ones achieved by dynamic programming to assess its convenience. |
| eu_rights_str_mv | openAccess |
| format | article |
| id | COLIBRI_584b3be991b5b6d3dcbad87f720170bd |
| identifier_str_mv | Vanerio, J. y Larroca, F. "Online expert-based prediction for cognitive radio secondary markets". IEEE Transactions on Cognitive Communications and Networking. [en línea]. 2020, vol. 6, no. 1, pp. 340-351. 2332-7731 |
| instacron_str | Universidad de la República |
| institution | Universidad de la República |
| instname_str | Universidad de la República |
| language | eng |
| language_invalid_str_mv | en |
| network_acronym_str | COLIBRI |
| network_name_str | COLIBRI |
| oai_identifier_str | oai:colibri.udelar.edu.uy:20.500.12008/47509 |
| publishDate | 2020 |
| reponame_str | COLIBRI |
| repository.mail.fl_str_mv | karina.camps@seciu.edu.uy |
| repository.name.fl_str_mv | COLIBRI - Universidad de la República |
| repository_id_str | 4771 |
| rights_invalid_str_mv | Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0) |
| spelling | Vanerio Juan Martín, Universidad de la República (Uruguay). Facultad de Ingeniería.Larroca Federico, Universidad de la República (Uruguay). Facultad de Ingeniería.2024-12-12T14:58:25Z2024-12-12T14:58:25Z2020Vanerio, J. y Larroca, F. "Online expert-based prediction for cognitive radio secondary markets". IEEE Transactions on Cognitive Communications and Networking. [en línea]. 2020, vol. 6, no. 1, pp. 340-351.2332-7731https://hdl.handle.net/20.500.12008/47509The growing importance of wireless communications drives an increasing interest in dynamic access to spectrum resources. This requires efficient management policies that allow spectrum sharing between licensed primary users (PU) and unlicensed secondary users (SU). On such scenario, PUs shall preserve their usage priority right over any SU. Also, no SU shall interfere on any PU. Technical viability can be achieved through Cognitive Radio devices that adjust their operating parameters adaptively. After discussing several economic and technical models to achieve efficient spectrum sharing, we propose an on-demand secondary market model regulated by a spectrum broker who controls resource allocation. This model provides economic incentives for both kind of users to cooperate: SUs are charged by the broker on behalf of PUs for resource utilization but are indemnified if expelled to ensure PU priority. We describe the main characteristics of such a system and address the question of what allocation decisions should the broker take in order to achieve economic benefit regardless of users behavior. Several online expert-based no-regret algorithms are proposed to guide the decision taking process and evaluated under different user behavior patterns. Their results are compared with the ones achieved by dynamic programming to assess its convenience.Submitted by Ribeiro Jorge (jribeiro@fing.edu.uy) on 2024-12-09T22:25:08Z No. of bitstreams: 2 license_rdf: 25790 bytes, checksum: 13adb202270a5f7cee03e795b33133c4 (MD5) VL20.pdf: 374123 bytes, checksum: e871f9c7662c1f6ff9df5d94f8f25a7e (MD5)Approved for entry into archive by Machado Jimena (jmachado@fing.edu.uy) on 2024-12-12T12:54:46Z (GMT) No. of bitstreams: 2 license_rdf: 25790 bytes, checksum: 13adb202270a5f7cee03e795b33133c4 (MD5) VL20.pdf: 374123 bytes, checksum: e871f9c7662c1f6ff9df5d94f8f25a7e (MD5)Made available in DSpace by Luna Fabiana (fabiana.luna@seciu.edu.uy) on 2024-12-12T14:58:25Z (GMT). No. of bitstreams: 2 license_rdf: 25790 bytes, checksum: 13adb202270a5f7cee03e795b33133c4 (MD5) VL20.pdf: 374123 bytes, checksum: e871f9c7662c1f6ff9df5d94f8f25a7e (MD5) Previous issue date: 202012 p.application/pdfenengIEEEIEEE Transactions on Cognitive Communications and Networking, vol. 6, no. 1, mar 2020, pp. 340-351.Las obras depositadas en el Repositorio se rigen por la Ordenanza de los Derechos de la Propiedad Intelectual de la Universidad de la República.(Res. Nº 91 de C.D.C. de 8/III/1994 – D.O. 7/IV/1994) y por la Ordenanza del Repositorio Abierto de la Universidad de la República (Res. Nº 16 de C.D.C. de 07/10/2014)info:eu-repo/semantics/openAccessLicencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0)Resource managementEconomicsBiological system modelingReal-time systemsCognitive radioPrediction algorithmsAdaptation modelsAccess controlDynamic spectrum accessDecision-makingCommunication system economicsOnline expert-based prediction for cognitive radio secondary markets.Artículoinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionreponame:COLIBRIinstname:Universidad de la Repúblicainstacron:Universidad de la RepúblicaVanerio, Juan MartínLarroca, FedericoTelecomunicacionesAnálisis de Redes, Tráficos y Estadísticas de Servicios (ARTES)LICENSElicense.txtlicense.txttext/plain; charset=utf-84267http://localhost:8080/xmlui/bitstream/20.500.12008/47509/5/license.txt6429389a7df7277b72b7924fdc7d47a9MD55CC-LICENSElicense_urllicense_urltext/plain; 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- Universidad de la Repúblicafalse |
| spellingShingle | Online expert-based prediction for cognitive radio secondary markets. Vanerio, Juan Martín Resource management Economics Biological system modeling Real-time systems Cognitive radio Prediction algorithms Adaptation models Access control Dynamic spectrum access Decision-making Communication system economics |
| status_str | publishedVersion |
| title | Online expert-based prediction for cognitive radio secondary markets. |
| title_full | Online expert-based prediction for cognitive radio secondary markets. |
| title_fullStr | Online expert-based prediction for cognitive radio secondary markets. |
| title_full_unstemmed | Online expert-based prediction for cognitive radio secondary markets. |
| title_short | Online expert-based prediction for cognitive radio secondary markets. |
| title_sort | Online expert-based prediction for cognitive radio secondary markets. |
| topic | Resource management Economics Biological system modeling Real-time systems Cognitive radio Prediction algorithms Adaptation models Access control Dynamic spectrum access Decision-making Communication system economics |
| url | https://hdl.handle.net/20.500.12008/47509 |